Synchronization Process Research Articles

A missed regular sound change between Latin and French

Abstract This paper presents evidence for a regular sound change in 12th-century Old French where word-initial /k/ voiced to /ɡ/ before /la/ or /ra/. My treatment is the first to propose a unified account, as due to a regular sound change, for 13 reflexes of inherited etyma and 4 reflexes of Germanic borrowings that all exhibit velar onset voicing (VOV) contemporaneously. A dating in the late 12th century for VOV is supported by both corpus evidence and how it is bled, counterbled, and fed by other sound changes whose dating is established in prior literature. The ultimate origins of this Old French velar onset voicing most likely lie in an older and phonetically conditioned synchronic voicing process that originally operated both word-internally and at boundaries. Word-internally, where conditioning was static, the alternation became a phonemic difference and thereafter lost productivity relatively early. But synchronic alternation continued at boundaries, where its conditioning continued to depend on the adjacent word. It survived in a progressively reshaped manner word-initially, until the late 12th century, when this voicing alternation, now much narrower in scope, gave rise to VOV as a regular diachronic sound change. Previous treatment of the words in question considered each only in isolation, bypassing the chance to consider the proposed regular sound change as a possibility. Thus, this study shows the importance of considering both lexically focused approaches and the probing for regular sound changes as necessarily complementary methods.

Implementing the procedure of measurement phase difference of the model signals using a virtual laboratory practicum

As this virtual laboratory practicum, which is a tool for mastering theoretical principles and practical skills in digital signal processing, was developed, users (mainly students) were given the possibility to parameterize harmonic signals. It includes the determination of the number of samples, sampling rate, amplitudes, initial phases, and other characteristics necessary for accurate metrological measurements. This publication presents the structure of the virtual workshop and the mathematical model underlying it, with an emphasis on aspects of analyzing the procedures for measuring the phase difference of harmonic signal models using the Discrete Fourier Transform. Particular attention is focused on the phase correction algorithm, which is aimed at improving the accuracy of measurements of the phase difference of signals. The presented methodology describes in detail the measurement process, estimation of errors arising from limited measurement time due to non-synchronization, the influence of the initial phase values of signals, and shows how the synchronization process contributes to a significant increase in the accuracy of measuring informative parameters.

A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddlers.

Early-life gut microbiota development depends on a highly synchronized microbial colonization process in which diet is a key regulator. Microbiota transition toward a more adult-like state in toddlerhood goes hand in hand with the transition from a milk-based diet to a family diet. Microbiota development during the first year of life has been extensively researched; however, studies during toddlerhood remain sparse. Young children's requirement for micronutrients, such as dietary iron, is higher than adults. However, their intake is usually sub-optimal based on regular dietary consumption. The Child Health and Residence Microbes (CHaRM) study, conducted as an adjunct to the GUMLi (Growing Up Milk "Lite") trial, was a double-blind randomized controlled trial to investigate the effects on body composition of toddler milk compared to unfortified standard cow's milk in healthy children between 1 and 2 years of age in Brisbane (Australia). In this trial, fortified milk with reduced protein content and added synbiotics [Bifidobacterium breve M-16V, short-chain galactooligosaccharides, and long-chain fructooligosaccharides (ratio 9:1)] and micronutrients were compared to standard unfortified cow's milk. In the present study, the effects of the intervention on the gut microbiota and its relationship with iron status in toddlers were investigated in a subset of 29 children (18 in the Active group and 11 in the Control group) who completed the CHaRM study. The toddler microbiota consisted mainly of members of the phyla Firmicutes, Bacteroidota, and Actinobacteriota. The abundance of the B. breve species was quantified and was found to be lower in the Control group than in the Active group. Analysis of blood iron markers showed an improved iron status in the Active group. We observed a positive correlation between Bifidobacterium abundance and blood iron status. PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. This analysis showed that the abundance of predicted genes encoding for enterobactin, a class of siderophores specific to Enterobacteriaceae, is inversely correlated with the relative abundance of members of the genus Bifidobacterium. These findings suggest that healthy children who consume a young child formula fortified with synbiotics as part of a healthy diet have improved iron availability and absorption in the gut and an increased abundance of Bifidobacterium in their gut microbiome.

Pyramid quaternion discrete cosine transform based ConvNet for cancelable face recognition

The current face scanning era can quickly and conveniently attain identity authentication, but face images imply sensitive information simultaneously. Under such context, we introduce a novel cancelable face recognition methodology by using quaternion transform based convolutional network. Firstly, face images in different modalities (e.g., RGB and depth or near-infrared) are encoded into full quaternion matrix for synchronous processing. Based on the designed multiresolution quaternion singular value decomposition, we can obtain pyramid representation. Then they are transformed through random projection for making the process noninvertible. Even if the feature template is compromised, a new one can be generated. Subsequently, a three-stream convolutional network is developed to learn features, where predefined filters are stemmed from quaternion two-dimensional discrete cosine transform basis. Extensive experiments on the TIII-D, NVIE and CASIA datasets have demonstrated that the proposed method obtains competitive performance, also satisfies redistributable and irreversible.

A novel hybrid PD-FEM-FVM approach for simulating hydraulic fracture propagation in saturated porous media

To enhance the computational efficiency of fluid–solid coupling in peridynamics (PD), a hybrid modeling approach based on the classical Biot theory is proposed for simulating hydraulic crack propagation in saturated porous media. The deformation and damage of solids are described by the coupling of the finite element method (FEM) and PD. Based on Darcy’s law, the finite volume method (FVM) is used to describe fluid seepage and calculate pore water pressure. The mutual transfer of fluid pressure and solid deformation is realized through the transition layer between the solid layer and the fluid layer. Firstly, the effectiveness of the proposed method is verified by a porous media seepage simulation example. Secondly, the ability and efficiency of this method to simulate crack propagation in saturated porous media are verified by several examples of hydraulic fracturing of rock with a single pre-existing crack. Finally, the synchronous hydraulic fracturing process of rock with double cracks is simulated. The ability of this method to simulate the simultaneous propagation of multiple fractures in the rock under fluid–solid coupling is further illustrated. The aforementioned studies demonstrate that the novel hybrid PD-FEM-FVM approach not only ensures computational accuracy and effectiveness but also significantly enhances computational efficiency.

Numerical investigation of steering synchronization dynamics of laterally coupled laser array with monolithically-integrated external cold cavity

This study numerically explores the synchronization dynamics of a one-dimension edge-emitting laser array monolithically-integrated with an external cold cavity comprehensively, aiming to achieve an in-phase mode optical field. By employing the optical feedback rate equation, the impact of mutual feedback coefficient and coupling coefficient on the synchronization process are investigated thoroughly. The proposed external cold cavity, designed according to the Talbot effect, could significantly diminish the reflectivity of front facet through separated electrode structure, therefore facilitating the phase-locking process. Consequently, the study uncovers the effective regime for establishing in-phase mode operation. Additionally, the numerical analysis also reveals the vivid synchronization dynamic from a chaotic state to partially-phase-locked, then completely-phase-locked, and ultimately periodic oscillation. Furthermore, the impact of practical fabrication tolerances on the synchronization process are explored as well. Based on the simulation results, our work could offer valuable insights for steering the on-chip optical field and developing novel laser arrays with high beam quality.

Optimization of the Synchronous Pressurization Process for the Elimination of Double-Layer Oxide Film Defects

Optimization of the Synchronous Pressurization Process for the Elimination of Double-Layer Oxide Film Defects

A novel adaptive parameter zeroing neural network for the synchronization of complex chaotic systems and its field programmable gate array implementation

This article proposes a novel adaptive-parameter zeroing neural network (NAP-ZNN) to control the synchronization of complex chaotic systems. Different from previous zeroing neural networks (ZNNs), the NAP-ZNN model incorporates adaptive-parameter, a unique blend of time-varying convergence factor and fuzzy control parameter, which is adjusted continuously according to the real-time synchronizing error, offering greater flexibility. The NAP-ZNN model aims to address the time-varying problem in complex-valued domain, which is scarcely explored, it rapidly impels two complex chaotic systems to synchronize within predetermined time and effectively mitigates noise interference. Moreover, the upper bound of the convergence time is theoretically calculated in noiseless environments, and the disturbance-resistant property is demonstrated under various noisy disturbances. The control performance of NAP-ZNN model has been separately compared to other general ZNNs (NAP-ZNN synchronizes at 0.097 s while three general ZNNs spend 0.43 s, 0.78 s and 0.84 s, and only NAP-ZNN complete synchronization within 0.1 s under noisy interferences while general ZNNs fail) and the traditional adaptive control method through two synchronization simulation (RMSE of NAP-ZNN under sinusoidal noise is 3.165 × 10-3 while traditional is 3.383 at t = 1 s). The numerical outcomes clearly illustrate the superior performance of the NAP-ZNN model in comparison to other synchronization strategies. The hardware implementation of the NAP-ZNN model has been successfully realized through the Field Programmable Gate Array (FPGA), and the chaos synchronization process has been vividly captured via an oscilloscope, further reinforcing the practicality and effectiveness of the NAP-ZNN model.

Students' Behavior in the Learning Process Using Zoom Meeting Media: Problems and Solutions

Recent digital technologies have increased the flexibility of learning. Online learning is now seen as a good alternative, not a force anymore. Among all online learning media that can aid, Zoom is an interactive online learning media mainly used by lecturers to carry out synchronous learning processes when offline lectures cannot be carried out. Using Zoom, lecturers and students can interact synchronously, like face-to-face learning in class. Many studies have been conducted to see the impacts of online learning on students’ learning behaviors using various media, yet studies on how students behave while learning using Zoom have not yet been explored in more detail. This research aims to reveal how students behave in the learning process by using Zoom in English classes through a survey study. Data were collected through a questionnaire delivered online to some 142 English Department students of Universitas Negeri Padang who experienced online learning. They voluntarily took part in this survey. Carrying quantitative analysis, the research showed that most students did not follow the Zoom-mediated learning process as well as they did face-to-face learning, which was carried out offline, for various reasons. Several positive and negative behaviors were found when implementing the learning process using Zoom. Therefore, for the learning process to run well, it is necessary to agree on the ethics of the learning process by using Zoom. The findings of this research can provide a reference for making conventional ethics of online learning using Zoom or other media.

On the expressiveness and efficiency of guarded lists in Bach

Concurrency theory has received considerable attention, but mostly in the scope of synchronous process algebras such as CCS, CSP, and ACP. As another way of handling concurrency, data-based coordination languages aim to provide a clear separation between interaction and computation by synchronizing processes asynchronously by means of information being available or not on a shared space. Although these languages enjoy interesting properties, verifying program correctness remains challenging. In particular, model checking logic formulae is known to raise performance issues due to the state space explosion problem. In this paper, we propose a guarded list construct as a solution to address this problem. Beyond increasing performance, it also enriches the expressiveness of data-based coordination languages and allows for program transformations that further increase the speed of computations.

Environmental Impact of Waste Treatment and Synchronous Hydrogen Production: Based on Life Cycle Assessment Method.

Based on the life cycle assessment methodology, this study systematically analyzes the energy utilization of environmental waste through photocatalytic treatment and simultaneous hydrogen production. Using 10,000 tons of organic wastewater as the functional unit, the study evaluates the material consumption, energy utilization, and environmental impact potential of the photocatalytic waste synchronous hydrogen production system (specifically, the synchronous hydrogen production process of 4-NP wastewater with CDs/CdS/CNU). The findings indicate that potential environmental impacts from the photochemical treatment of environmental waste and synchronous hydrogen production primarily manifest in freshwater ecological toxicity, marine ecological toxicity, terrestrial ecological toxicity, and non-carcinogenic toxicity to humans. These ecological impacts stem from the catalyst's adsorption and metal leaching during the photo-degradation and hydrogen production processes of environmental waste. By implementing reasonable modifications and morphological refinements to the catalyst, these effects can be mitigated while achieving enhanced efficiency in environmental waste processing and simultaneous hydrogen production. The research outcomes provide valuable insights for advancing sustainable development in green technology for environmental waste treatment and energy utilization.

Synchronization processes in fNIRS visibility networks

We employ Kuramoto model to assess the presence of synchronization in individuals who fulfill a cooperation task. Our input data is a couple of signals obtained from functional Near-Infrared Spectroscopy Data Acquisition and Pre-processing technology that is used to capture the brain activity of an individual by measuring the oxyhemoglobin (HbO) level. We consider 1 min signal for individuals in three distinct states: (i) rest; (ii) before a disturb happens; (iii) after the disturbance. We estimate global and local order parameters synchronization with the purpose to compare the conditions of reaching a synchronous state in the networks corresponding to different states for distinct individuals and hemispheres of the prefrontal cortices of same individual. Experimental results confirmed once more that coherent state is reached not for same conditions in both individuals and hemispheres of the prefrontal cortices. Furthermore, condition changes even for different events. The computation of the effective frequencies for each degree class indicates clearly the network difference in rest, before and after disturb. Finally, we investigate the dynamic connectivity matrix and consider the similarity between distinct prefrontal cortices over time.

Developing Scalable APIs for Data Synchronization in Salesforce Environments

In the modern business landscape, Salesforce has become an essential platform for managing customer relationships, driving sales, and fostering business growth. However, as organizations grow and their data volumes increase, the need for efficient and scalable data synchronization across various systems becomes paramount. Developing scalable APIs for data synchronization in Salesforce environments presents a significant challenge due to the complexity of integrating multiple data sources, ensuring real-time updates, and maintaining data integrity across diverse systems. This paper explores the design and implementation of scalable APIs specifically tailored for data synchronization within Salesforce environments. It delves into the architectural considerations necessary for creating robust, high-performance APIs capable of handling large volumes of data while ensuring consistency and reliability. The discussion begins with an overview of Salesforce’s ecosystem, highlighting the importance of data synchronization in maintaining seamless operations across various departments and systems. A critical component of this study is the examination of different API design patterns that support scalability, such as RESTful services, GraphQL, and event-driven architectures. Each approach is analyzed for its suitability in handling the unique challenges of Salesforce data synchronization, such as managing API limits, optimizing data transfer, and ensuring that data synchronization processes do not disrupt ongoing business activities. The paper also explores the role of middleware solutions, like Enterprise Service Bus (ESB) and API gateways, in facilitating seamless data flow between Salesforce and other systems.

Beta bursts in the parkinsonian cortico-basal ganglia network form spatially discrete ensembles

Defining spatial synchronisation of pathological beta oscillations is important, given that many theories linking them to parkinsonian symptoms propose a reduction in the dimensionality of the coding space within and/or across cortico-basal ganglia structures. Such spatial synchronisation could arise from a single process, with widespread entrainment of neurons to the same oscillation. Alternatively, the partially segregated structure of cortico-basal ganglia loops could provide a substrate for multiple ensembles that are independently synchronized at beta frequencies. Addressing this question requires an analytical approach that identifies groups of signals with a statistical tendency for beta synchronisation, which is unachievable using standard pairwise measures. Here, we utilized such an approach on multichannel recordings of background unit activity (BUA) in the external globus pallidus (GP) and subthalamic nucleus (STN) in parkinsonian rats. We employed an adapted version of a principle and independent component analysis-based method commonly used to define assemblies of single neurons (i.e., neurons that are synchronized over short timescales). This analysis enabled us to define whether changes in the power of beta oscillations in local ensembles of neurons (i.e., the BUA recorded from single contacts) consistently covaried over time, forming a “beta ensemble”. Multiple beta ensembles were often present in single recordings and could span brain structures. Membership of a beta ensemble predicted significantly higher levels of short latency (<5 ms) synchrony in the raw BUA signal and phase synchronisation with cortical beta oscillations, suggesting that they comprised clusters of neurons that are functionally connected at multiple levels, despite sometimes being non-contiguous in space. Overall, these findings suggest that beta oscillations do not comprise of a single synchronisation process, but rather multiple independent activities that can bind both spatially contiguous and non-contiguous pools of neurons within and across structures. As previously proposed, such ensembles provide a substrate for beta oscillations to constrain the coding space of cortico-basal ganglia circuits.

Quenches in the Sherrington–Kirkpatrick model

The Sherrington–Kirkpatrick model is a prototype of a complex non-convex energy landscape. Dynamical processes evolving on such landscapes and locally aiming to reach minima are generally poorly understood. Here, we study quenches, i.e. dynamics that locally aim to decrease energy. We analyse the energy at convergence for two distinct algorithmic classes, single-spin flip and synchronous dynamics, focusing on greedy and reluctant strategies. We provide precise numerical analysis of the finite size effects and conclude that, perhaps counter-intuitively, the reluctant algorithm is compatible with converging to the ground state energy density, while the greedy strategy is not. Inspired by the single-spin reluctant and greedy algorithms, we investigate two synchronous time algorithms, the sync-greedy and sync-reluctant algorithms. These synchronous processes can be analysed using dynamical mean field theory (DMFT), and a new backtracking version of DMFT. Notably, this is the first time the backtracking DMFT is applied to study dynamical convergence properties in fully connected disordered models. The analysis suggests that the sync-greedy algorithm can also achieve energies compatible with the ground state, and that it undergoes a dynamical phase transition.

Design of an integrated network order system for main distribution network considering power dispatch efficiency

This study presents a comprehensive review of the primary distribution design of an advanced network control system, emphasizing its evolution from initial requirements to practical applications. The system solves complex problems of power management by combining real-time data analysis, intelligent decision making for resource allocation, rapid fault correction, remote monitoring and complex optimization methods, all aimed at ensuring stable and safe operation of the power grid. Its performance is geared towards fast response, efficient data processing and synchronous processing tasks, ensuring smooth operation even under heavy workloads. Security is enhanced through strict protocols, encryption methods, and controlled access systems. The system is divided into four layers-data collection, communication, decision-making and application management-using innovative tools such as Kalman filters and deep Q networks. The research showcases the integrated network command system’s prowess, achieving an average response time of 0.27 s, 98.5% dispatching accuracy, and 83.2% resource utilization, evidencing exceptional performance. It excels under various tests, including managing high loads with minimal accuracy loss, rapidly adapting to changes with a hydro model response time of 0.22 s, efficiently integrating renewables at 78.0% efficiency, and proving resilient in peak hours, affirming its capability to bolster grid efficiency, reliability, and integration of renewable energy resources. By outlining these specific achievements, this case study not only illustrates the complex design of the system, but also highlights its great potential for improving grid resilience and efficiency, attracting a wide audience interested in the future of energy management.

Synchronized Shared Memory and Black-box Procedural Abstraction: Toward a Formal Semantics of Blech

Traditional imperative synchronous programming languages heavily rely on a strict separation between data memory and communication signals. Signals can be shared between computational units but cannot be overwritten within a synchronous reaction cycle. Memory can be destructively updated but cannot be shared between concurrent threads. This incoherence makes traditional imperative synchronous languages cumbersome for the programmer. The recent definition of sequentially constructive synchronous languages offers an improvement. It removes the separation between data memory and communication signals and unifies both through the notion of clock synchronized shared memory . However, it still depends on global causality analyses, which precludes black-box procedural abstraction. This complicates reuse and composition of software components. This article shows how black-box procedural abstraction can be accommodated inside the sequentially constructive model of computation. We present the Sequentially Constructive Procedural Language ( SCoPL ) and its semantic theory of policy-constructive synchronous processes. SCoPL supports black-box procedural abstractions using policy interfaces to ensure that procedure calls are memory-safe and wait-free and their scheduling is determinate and causal. At the same time, a policy interface constrains the level of freedom for the implementation and subsequent refactoring of a procedure. As a result, policies enable separate compilation and composition of procedures. We present our extensions abstractly as a formal semantics for SCoPL and motivate it concretely in the context of the open-source, embedded, real-time language Blech .

A cooperative timestamp-free clock synchronization scheme based on fast unscented Kalman filtering for time-sensitive networking

Clock synchronization, built on the classical two-way message exchange scheme, is the key prerequisite for the normal operation of time-sensitive networking (TSN). In practical TSN, the imperfect oscillator caused by environmental changes leads to clock parameters drift. Moreover, synchronization errors accumulate in multi-hop networks, making it difficult for nodes at the edge of the network to achieve precise synchronization performance. Additionally, in some industrial and vehicular scenarios, the energy consumption and complexity of clock synchronization are important factors that need to be considered. To address these problems, this paper proposes a cooperative synchronization clock offset and clock skew joint tracking algorithm based on fast Unscented Kalman filter (FUKF). To further reduce the computation and energy consumption caused by clock synchronization, we introduce randomized singular value decomposition and timestamp-free exchange. The former uses small sub-matrices approximations to replace extremely high-dimensional matrices, reducing computational time in the update stage of the UKF. The latter reduces energy consumption by setting response intervals at the receiving end, eliminating the need for timestamp exchange during the synchronization process. Therefore, this algorithm can achieve long-term synchronization without requiring excessive computational and communication overhead. The results show that the proposed method, while maintaining accuracy unchanged, reduced the running time by 20% to 90% as the number of observations increased, thus verifying the effectiveness of the algorithm.

Continuous and synchronous calibration process of ovality and straightness for longitudinally submerged arc welding pipes with three rollers.

A new process of continuous and synchronous calibration process of ovality and straightness for LSAW (Longitudinally Submerged Arc Welding, LSAW) pipes with three rollers is proposed. Specifically, the process is introduced from three aspects: roller-shape, loading parameters and axial and circumferential deformation paths. The process is verified by numerical simulation and physical experiments. Further, the stress-strain in the Sections Ⅱ and Ⅳ is analyzed. The relationship between the process parameters and the residual ovality and residual straightness by experiments is discussed. The calibration scheme of LSAW pipes is put forward by using the control variable method. The results show that the shear stress is the principal stress direction in the Sections Ⅱ and Ⅳ. The residual ovality and residual straightness decrease with the increase of the radial reduction and times of reciprocating bending. The reciprocating bending process can eliminate the difference of the initial curvature, make the curvature of each section tend to be uniform. After calibration, the residual straightness is less than 0.2% and the residual ovality is less than 1%, demonstrating a good feasibility of this process.

Study of a Numerical Integral Interpolation Method for Electromagnetic Transient Simulations

In the fixed time-step electromagnetic transient (EMT)-type program, an interpolation process is applied to deal with switching events. The interpolation method frequently reduces the algorithm’s accuracy when dealing with power electronics. In this study, we use the Butcher tableau to analyze the defects of linear interpolation. Then, based on the theories of Runge–Kutta integration, we propose two three-stage diagonally implicit Runge–Kutta (3S-DIRK) algorithms combined with the trapezoidal rule (TR) and backward Euler (BE), respectively, with TR-3S-DIRK and BE2-3S-DIRK for the interpolation and synchronization processes. The proposed numerical integral interpolation scheme has second-order accuracy and does not produce spurious oscillations due to the size change in the time step. The proposed method is compared with the critical damping adjustment method (CDA) and the trapezoidal method, showing that it does not produce spurious numerical oscillations or first-order errors.